Predictive maintenance system, predictive maintenance method, and predictive maintenance computer program

Abstract

An aspect relates to providing a predictive maintenance technique for managing relay service life of train onboard unit relay racks not equipped with operation count functionality. The predictive maintenance method includes collecting a set of onboard unit data including at least a set of command data indicating a set of commands output by a control computer to a set of relay racks to operate the set of relays, generating a command relay list, determining a relay operation count indicating a number of operations for each relay based on the command relay list and the set of command data, and determining a maintenance action for a first relay rack of the set of relay racks when the relay operation count for the first relay rack exceeds a predetermined threshold.

Description

Technical Field

[0001] The present disclosure relates to a predictive maintenance system, a predictive maintenance method, and a predictive maintenance computer program.

Background Art

[0002] In recent years, as railway systems have become increasingly sophisticated, the importance of reliably monitoring, collecting, and communicating information related to the operation of railway vehicles in a train formation has similarly increased. By analyzing the operation information collected from railway vehicle systems, useful insights regarding the efficiency and safety of operations can be obtained.

[0003] Conventionally, techniques for analyzing railway vehicle operation data to detect anomalies have been considered. As an example of a railway vehicle data anomaly technique, European Patent Application Publication No. 3988423 (Patent Document 1) discloses "a monitoring system for a railway network, a server, a method, and a bimodal railway vehicle, the monitoring system being configured to operate in both electrified and non-electrified sections, one or more bimodal railway vehicles of the railway network, one or more beacons located at respective line points and configured to broadcast a beacon signal indicating a transition from an electrified section of the railway network to a non-electrified section of the railway network or vice versa, and a server configured to receive from a given beacon one or both of a beacon signal received by a given bimodal railway vehicle from the given beacon and a position signal indicating the position of the given bimodal railway vehicle in the railway network, the server being further configured to determine whether a given beacon, a given bimodal railway vehicle, or a further bimodal railway vehicle is defective from the received beacon signal and / or the received position signal."

Prior Art Documents

Patent Documents

[0004] [Patent Document 1] European Patent Application Publication No. 3988423 [Overview of the Initiative] [Problems that the invention aims to solve]

[0005] In modern railway systems, trains are often equipped with onboard units (OBUs) to facilitate train communication and control operations. Generally, these OBUs include a relay rack, each containing multiple relays, and a control computer that issues commands to the relays in the set of relay racks to perform various train control functions. For example, the relay rack may include relays to monitor and collect sensor data, communicate with along-track devices, and perform signal transmission operations, brake control, etc.

[0006] Each relay installed within a relay rack is associated with a service life. A relay's service life can be expressed in terms of the estimated number of operations a given relay will perform before failure or replacement. Since unexpected relay failures can cause problems with train communication, signaling, braking, or other operational functions, it is desirable to track the number of operations for each relay to facilitate maintenance and replacement before the relay reaches the end of its service life. Therefore, some relays are equipped with counters that track the number of times they have operated.

[0007] However, not all relays are equipped with an operation counting function. Limiting the use of relays to those with an operation counting function may restrict the functionality of the relays and increase the relay installation cost. Patent Document 1 discloses a technique for distinguishing whether a communication failure with a railway vehicle is due to a malfunction of the railway vehicle or a malfunction of the railway device, but it does not consider or disclose a technique for performing predictive maintenance with respect to OBU relays that are not equipped with an operation counting function.

[0008] Therefore, the purpose of this disclosure is to provide a predictive maintenance technique for managing the relay service life of an OBU relay rack that is not equipped with an operation counting function. [Means for solving the problem]

[0009] One representative example of the present disclosure relates to a predictive maintenance system for a train-mounted unit, the predictive maintenance system comprising a train-mounted unit disposed on a train, and a predictive maintenance device for determining maintenance actions for the train-mounted unit, wherein the train-mounted unit includes a set of relay racks, each containing a set of relays, and includes a control computer for outputting commands to operate the sets of relays in the set of relay racks, but does not include a relay operation count function for counting the number of operations of the sets of relays, and the predictive maintenance device includes a data acquisition unit for collecting a set of onboard unit data, which includes at least a set of command data indicating a set of commands output by the control computer to the set of relay racks to operate the sets of relays, a data management unit for generating a command relay list indicating the relationship between the sets of commands and the sets of relays operating for each command, a data analysis unit for determining a relay operation count indicating the number of operations for each relay in the set of relays based on the command relay list and the set of command data, and a maintenance management unit for determining maintenance actions for a first relay rack when the relay operation count of a first relay rack among the sets of relay racks exceeds a predetermined threshold. [Effects of the Invention]

[0010] According to this disclosure, it is possible to provide a predictive maintenance technique for managing the relay service life of an OBU relay rack that is not equipped with an operation counting function.

[0011] Any other issues, configurations, and effects not mentioned above will become apparent from the following description of embodiments for carrying out the present invention. [Brief explanation of the drawing]

[0012] [Figure 1] This figure shows an exemplary computing architecture for executing embodiments of the present disclosure. [Figure 2] This figure shows an example hardware configuration of a predictive maintenance system according to an embodiment of the present disclosure. [Figure 3] This is a flowchart showing a predictive maintenance method according to an embodiment of the disclosure. [Figure 4] This figure shows a correspondence table according to the embodiments of this disclosure. [Figure 5] This figure shows a list of command relays according to the embodiments of this disclosure. [Figure 6] This figure shows the set of relay operation count data according to the embodiment of the disclosure. [Figure 7] This figure shows the set of relay operation count threshold data according to the embodiment of this disclosure. [Figure 8] This figure shows a rack error list according to an embodiment of the disclosure. [Figure 9] This figure shows the error count data according to the embodiment of the disclosure. [Figure 10] This figure shows the set of relay rack usage data according to the embodiment of this disclosure. [Modes for carrying out the invention]

[0013] Embodiments of the present invention will be described below with reference to the drawings. It should be noted that the embodiments described herein are not intended to limit the present invention to the claims, and that the elements and combinations described in relation to the embodiments are not strictly essential for realizing the aspects of the present invention.

[0014] Various aspects are disclosed in the following description and the related drawings. Alternative aspects may be devised without departing from the scope of the present disclosure. Additionally, well-known elements of the present disclosure may not be described in detail or may be omitted so as not to obscure the relevant details of the present disclosure.

[0015] The phrases "exemplary" and / or "example" are used herein to mean "serving as an example, instance, or illustration." Any aspect described herein as "exemplary" and / or "example" is not necessarily to be construed as preferred or advantageous over other aspects. Similarly, the term "aspect of the present disclosure" does not require that all aspects of the present disclosure include the features, advantages, or modes of operation being considered.

[0016] Furthermore, for example, with respect to a series of actions performed by elements of a computing device, many aspects are described. It will be recognized that the various actions described herein can be implemented by a particular circuit (e.g., an application specific integrated circuit (ASIC)), by program instructions executed by one or more processors, or by a combination of both. Additionally, the series of actions described herein can be considered to be embodied in their entirety within any form of computer-readable storage medium storing a corresponding set of computer instructions that, when executed, cause the associated processor to perform the functions described herein. Accordingly, the various aspects of the present disclosure may be embodied in many different forms, and all such forms are contemplated to be within the scope of the claimed subject matter.

[0017] Details of embodiments of the present disclosure will be described below with reference to the drawings.

[0018] Turning now to the drawings, FIG. 1 shows a high-level block diagram of a computer system 100 for implementing various embodiments of the present disclosure, according to an embodiment. The mechanisms and apparatus of the various embodiments disclosed herein are equally applicable to any suitable computing system. The main components of the computer system 100 include one or more processors 102, a memory 104, a terminal interface 112, a storage interface 113, an I / O (input / output) device interface 114, and a network interface 115, all of which are communicatively coupled, either directly or indirectly, for component-to-component communication via a memory bus 106, an I / O bus 108, a bus interface unit 109, and an I / O bus interface unit 110.

[0019] The computer system 100 may include one or more general-purpose programmable central processing units (CPUs) 102A and 102B, generically referred to herein as processors 102. In an embodiment, the computer system 100 may include multiple processors, although in a particular embodiment, the computer system 100 may alternatively be a single CPU system. Each processor 102 executes instructions stored in the memory 104 and may include one or more levels of on-chip cache.

[0020] In some embodiments, memory 104 may include random-access semiconductor memory, storage devices, or storage media (either volatile or non-volatile) for storing or encoding data and programs. In certain embodiments, memory 104 may represent the entire virtual memory of computer system 100 and may also include the virtual memory of other computer systems coupled to or connected to computer system 100 via a network. While memory 104 can be conceptually viewed as a single monolithic entity, in other embodiments, memory 104 has a more complex configuration, such as a hierarchy of caches and other memory devices. For example, memory may exist in the form of multiple levels of caches, which may be further divided by function, such that one cache holds instructions and another cache holds data other than instructions used by one or more processors. Memory may also be distributed and associated with different CPUs or sets of CPUs, as is known in various so-called non-uniform memory access (NUMA) computer architectures.

[0021] Memory 104 may store all or part of various programs, modules, and data structures for handling data transfers as discussed herein. For example, memory 104 can store a predictive maintenance application 150. In embodiments, the predictive maintenance application 150 may include instructions or statements executed by the processor 102, or instructions or statements interpreted by instructions or statements executed by the processor 102, in order to perform functions further described below. In certain embodiments, the predictive maintenance application 150 is implemented in hardware, via semiconductor devices, chips, logic gates, circuits, circuit cards, and / or other physical hardware devices, instead of, or in addition to, a processor-based system. In embodiments, the predictive maintenance application 150 may include data in addition to instructions or statements. In certain embodiments, a camera, sensor, or other data input device (not shown) may be provided, communicating directly with the bus interface unit 109, the processor 102, or other hardware of the computer system 100. In such a configuration, the need for the processor 102 to access the memory 104 and the predictive maintenance application 150 may be reduced.

[0022] The computer system 100 may include a bus interface unit 109 that handles communication between the processor 102, memory 104, display system 124, and I / O bus interface unit 110. The I / O bus interface unit 110 may be coupled to the I / O bus 108 to transfer data to and from various I / O units. The I / O bus interface unit 110 communicates with a plurality of I / O interface units 112, 113, 114, and 115, also known as I / O processors (IOPs) or I / O adapters (IOAs), through the I / O bus 108. The display system 124 may include a display controller, display memory, or both. The display controller may provide video, audio, or both types of data to the display device 126. Furthermore, the computer system 100 may include one or more sensors or other devices configured to collect data and provide it to the processor 102. For example, the computer system 100 may include biometric sensors (e.g., for collecting heart rate data, stress level data), environmental sensors (e.g., for collecting humidity data, temperature data, pressure data), motion sensors (e.g., for collecting acceleration data, motion data), etc. Other types of sensors are also possible. The display memory may be dedicated memory for buffering video data. The display system 124 may be coupled with a display device 126, such as a standalone display screen, a computer monitor, a television, or a tablet or mobile device display. In one embodiment, the display device 126 may include one or more speakers for rendering sound. Alternatively, one or more speakers for rendering sound may be coupled with an I / O interface unit. In an alternative embodiment, one or more of the functions provided by the display system 124 may also be implemented in an integrated circuit including a processor 102. In addition, one or more of the functions provided by the bus interface unit 109 may also be implemented in an integrated circuit including a processor 102.

[0023] The I / O interface unit supports communication with various storage and I / O devices. For example, the terminal interface unit 112 supports the attachment of one or more user I / O devices 116, which may include user output devices (such as video display devices, speakers, and / or televisions) and user input devices (such as keyboards, mice, keypads, touchpads, trackballs, buttons, light pens, or other pointing devices). The user may use the user interface to operate the user input devices and receive output data via the user output devices in order to provide input data and commands to the user I / O devices 116 and the computer system 100. For example, the user interface may be presented via the user I / O devices 116, such as being displayed on a display device, played through speakers, or printed through a printer.

[0024] The storage interface 113 supports the attachment of one or more disk drives or direct-access storage devices 117 (typically rotating magnetic disk drive storage devices, or arrays of disk drives configured to appear as a single large storage device to the host computer, or other storage devices including solid-state drives such as flash memory). In some embodiments, the storage device 117 may be implemented via any type of secondary storage device. The contents of memory 104, or any part thereof, may be stored in and retrieved from the storage device 117 as needed. The I / O device interface 114 provides an interface to various other I / O devices or other types of devices such as printers or facsimile machines. The network interface 115 provides one or more communication paths from the computer system 100 to other digital devices and computer systems, and these communication paths may include, for example, one or more networks 130.

[0025] The computer system 100 shown in Figure 1 illustrates a specific bus structure that provides direct communication paths between the processor 102, memory 104, bus interface 109, display system 124, and I / O bus interface unit 110. However, in alternative embodiments, the computer system 100 may include different buses or communication paths that are arranged in any of various forms, such as point-to-point links in a hierarchical, star, or web configuration, multi-tier buses, parallel or redundant paths, or any other suitable type of configuration. Furthermore, although the I / O bus interface unit 110 and I / O bus 108 are shown as single units, the computer system 100 may actually encompass multiple I / O bus interface units 110 and / or multiple I / O buses 108. Multiple I / O interface units are shown that isolate the I / O bus 108 from various communication paths leading to various I / O devices. However, in other embodiments, some or all of the I / O devices are directly connected to one or more system I / O buses.

[0026] In various embodiments, the computer system 100 is a multi-user mainframe computer system, a single-user system, or a server computer, or a similar device that has little or no direct user interface but receives requests from other computer systems (clients). In other embodiments, the computer system 100 may be implemented as a desktop computer, a portable computer, a laptop or notebook computer, a tablet computer, a pocket computer, a telephone, a smartphone, or any other suitable type of electronic device.

[0027] Next, with reference to Figure 2, an example hardware configuration of a railway vehicle data analysis system according to an embodiment of the present disclosure will be described.

[0028] Figure 2 shows an exemplary hardware configuration of a predictive maintenance system 200 according to an embodiment of the present disclosure. The predictive maintenance system 200 relates to an information processing system configured to collect a set of onboard unit data from onboard units of a railway vehicle, generate a command relay list showing the relationship between a set of commands and the relays that operate for each command based on the set of onboard unit data, determine a relay operation count showing the number of operations for each relay, and determine a maintenance action for one or more relay racks based on at least the relay operation count.

[0029] As shown in Figure 2, the predictive maintenance system 200 according to an embodiment of the present disclosure includes a railway vehicle 210, a user terminal 220, a communication network 230, and a predictive maintenance device 240. In the predictive maintenance system 200, the railway vehicle 210, the user terminal 220, and the predictive maintenance device 240 may be communicated together via the communication network 230. Here, the communication network 230 may include local area network (LAN) connections, the Internet, wide area network (WAN) connections, metropolitan area network (MAN) connections, and the like.

[0030] In embodiments, the railway vehicle 210 may include one or more railway vehicles, such as trains, that are coupled or connected to each other and move along a track extending along a route. Alternatively, the vehicles do not have to be mechanically coupled to each other, but they may communicate with each other so that they coordinate their movement and the group of vehicles move together along the route in a coordinated manner. The railway vehicle 210 may be used in operations described as freight rail, passenger rail, high-speed rail, commuter rail, rail transport, subway, light rail, tram, tram line, or tramtrain.

[0031] The railway vehicle 210 may include one or more onboard units (OBUs) 215, where OBU 215 refers to a device installed in the railway vehicle 210 that is configured to perform various functions to facilitate railway vehicle communication and operational control operations. In embodiments, the OBU 215 may be configured to collect a set of onboard unit data that characterizes the operation of the OBU 215. In embodiments, the OBU 215 may transmit the set of onboard unit data to a user terminal and / or predictive maintenance device 240 via a communication network 230. In certain embodiments, the OBU 215 may store the set of onboard unit data for collection in local storage (e.g., an SD card, a hard drive, etc.) after the operation of the railway vehicle 210 is complete. As shown in Figure 2, the OBU 215 includes a control computer 216 and a set of relay racks 217.

[0032] The control computer 216 is a computing device configured to communicate with user terminals, predictive maintenance devices 240, railway line devices, and other external devices, and to issue commands to the relays of the relay rack set 217. The relay rack set 217 includes a structure for housing a set of relays. Each relay rack (1, 2, n) in the relay rack set 217 may contain a set of relays. These relays may be electrically operated switches associated with one or more railway vehicle functions configured to operate in response to specific commands from the control computer 216. For example, the relay rack set 217 may include relays for monitoring and collecting sensor data, communicating with railway devices, and performing signal transmission operations, brake control, etc.

[0033] The user terminal 220 is a device that can be used by a user (e.g., a client) of the predictive maintenance device 240. In an embodiment, the user terminal 220 may be used to request analysis of a set of in-vehicle unit data collected from the OBU 215 by the predictive maintenance device 240 and to confirm the results of this analysis. For example, the user terminal 220 may be implemented using a personal computer, tablet computer, smartphone, or other computing device.

[0034] The predictive maintenance device 240 is configured to collect and analyze a set of in-vehicle unit data to manage the service life of each relay in a set of relays in a set of relay racks 217 of the OBU 215. In embodiments, the predictive maintenance device 240 may be implemented using the computer system 100 shown in Figure 1 as part of a distributed computing architecture. For example, the functionality of the predictive maintenance device 240 may be implemented using one or more computing devices (e.g., the computer system 100 shown in Figure 1) with a cloud infrastructure.

[0035] As shown in Figure 2, the predictive maintenance device 240 may include a data acquisition unit 242, a data management unit 244, a data analysis unit 246, a maintenance management unit 248, and a storage unit 250. In some embodiments, the data acquisition unit 242, the data management unit 244, the data analysis unit 246, and the maintenance management unit 248 may be implemented as software modules that construct a predictive maintenance application 150 stored in the memory 104 of the computer system 100 shown in Figure 1. In this way, the functions of the data acquisition unit 242, the data management unit 244, the data analysis unit 246, and the maintenance management unit 248 can be implemented by the processor 102 of the computer system 100 to realize the technique of this disclosure.

[0036] The data acquisition unit 242 is a functional unit for acquiring a set of onboard unit data for the OBU 215 of the railway vehicle 210. The onboard unit data may include at least a set of command data indicating a set of commands output by the control computer 216 to a set of relay racks 217 to operate a set of relays. In an embodiment, the data acquisition unit 242 may acquire the set of onboard unit data from a user terminal 220. For example, a user of the user terminal 220 may upload the set of onboard unit data to the predictive maintenance device 240 via a graphical user interface provided by the data acquisition unit 242. In an embodiment, the data acquisition unit 242 may directly send a data acquisition request to the railway vehicle 210 in order to acquire the set of onboard unit data. In a particular embodiment, the data acquisition unit 242 may acquire the set of onboard unit data collected from the OBU 215 from a local storage device (e.g., an SD card, a hard drive, etc.) after the operation of the railway vehicle 210 is complete.

[0037] The data management unit 244 is a functional unit for organizing and manipulating sets of onboard unit data together with other pre-prepared data to facilitate analysis. The data management unit 244 may generate correspondence tables showing the relationships between specific train onboard units, sets of relay racks included in the train onboard units, and sets of relays in each relay rack within the set of relay racks. In embodiments, the data management unit 244 may generate a command relay list showing the relationships between sets of commands and sets of relays that operate for each command. In addition, in embodiments, the data management unit 244 may generate a rack error list showing the relationships between error types and sets of relay racks. The data generated by the data management unit 244 may be stored in the storage unit 250.

[0038] The data analysis unit 246 is a functional unit for performing analysis on a set of in-vehicle unit data and other intermediate data generated by the data management unit to determine information regarding the service life of the relay rack set 217 of the OBU 215. In embodiments, the data analysis unit 246 may determine a relay operation count indicating the number of operations for each relay in the relay rack set 217 based on a command relay list generated by the data management unit 244 and a set of command data included in the in-vehicle unit data. In addition, in embodiments, the data analysis unit 246 may determine an error count indicating the number of errors for each rack in the relay rack set 217, and / or operation time data indicating the operating duration of the relay rack set 217 of the OBU 215.

[0039] The maintenance management unit 248 is a functional unit for determining maintenance actions for one or more relay frames in the set of relay frames 217 based on information about the service life of the set of relay frames 217 generated by the data analysis unit 246. In an embodiment, the maintenance management unit 248 may determine a maintenance action for the first relay frame in the set of relay frames 217 if the relay operation count, error count, or operation time of the first relay frame exceeds a predetermined threshold.

[0040] The storage unit 250 is a unit for storing various data and information used to implement an aspect of this disclosure. The storage unit 250 may include a collection of hard disk drives, solid-state drives, flash memory, cloud storage, etc. As shown in Figure 2, the storage unit 250 may include a correspondence table, a command relay list, a rack error list, and a set of relay rack usage data. Details of the correspondence table, command relay list, rack error list, and set of relay rack usage data will be described later, so their explanation is omitted here. Furthermore, it should be noted that the contents of the storage unit 250 are not limited, and the storage unit 250 may include information other than the command relay list, rack error list, and set of relay rack usage data.

[0041] According to the predictive maintenance system 200 shown in Figure 2, it is possible to provide a predictive maintenance technique for managing the relay service life of OBU relay racks that are not equipped with an operation counting function.

[0042] Next, with reference to Figure 3, a predictive maintenance method according to an embodiment of this disclosure will be described.

[0043] Figure 3 shows a predictive maintenance method 300 according to an embodiment of the present disclosure. The predictive maintenance method 300 is a method for determining maintenance actions for one or more relay racks of an OBU based on the usage characteristics of the OBU's relay racks. The predictive maintenance method 300 may be implemented by various functional units of the predictive maintenance device 240 shown in Figure 2.

[0044] First, in step S305, the data acquisition unit 242 of the predictive maintenance device 240 acquires a set of onboard unit data. As described herein, the set of onboard unit data is a set of data characterizing the operation of a specific OBU (e.g., OBU 215 shown in Figure 2) installed on a railway vehicle. The set of onboard unit data may include at least a set of command data indicating a set of commands output by the control computer 216 of the OBU 215 to a set of relay racks 217 to operate a set of relays. In addition, in embodiments, the set of onboard unit data may include a set of error data indicating the presence or absence of errors for each rack of the set of relay racks. Furthermore, in embodiments, the set of onboard unit data may include a set of operation time data indicating the operating duration of the set of relay racks of the train onboard unit. In certain embodiments, the set of onboard unit data may include OBU identification information that identifies the origin of the set of onboard unit data.

[0045] In one embodiment, the data acquisition unit 242 may acquire a set of on-board unit data from a user terminal 220. For example, the user of the user terminal 220 may upload the set of on-board unit data to the predictive maintenance device 240 via a graphical user interface provided by the data acquisition unit 242. In another embodiment, the data acquisition unit 242 may directly send a data acquisition request to the railway vehicle 210 in order to dynamically acquire the set of on-board unit data in real time. In a particular embodiment, the data acquisition unit 242 may acquire the set of on-board unit data collected from the OBU 215 from a local storage device (e.g., an SD card, hard drive, etc.) after the operation of the railway vehicle 210 is complete.

[0046] Next, in step S310, the data management unit 244 of the predictive maintenance device 240 generates a correspondence table showing the relationships between a specific train onboard unit, a set of relay racks included in the train onboard unit, and a set of relays in each relay rack. The data management unit 244 may generate the correspondence table based on a set of onboard unit data and a pre-prepared set of relay rack identification information. The set of relay rack identification information may include information such as a rack type indicating the type of relay rack, a rack serial number that uniquely identifies a specific relay rack, and relay name information that identifies a specific relay installed on the relay rack by a specific rack serial number. In an embodiment, the data management unit 244 may generate the correspondence table by associating the set of relay rack identification information with a specific OBU number based on the OBU identification information included in the set of onboard unit data. In this way, a correspondence table showing the relationships between OBUs, relay racks, and relays for each railway vehicle in the railway network can be determined and maintained by the predictive maintenance device 240.

[0047] Next, in step S315, the data management unit 244 generates a command relay list showing the relationship between the set of commands included in the in-vehicle unit data received in step S305 (for example, a set of commands issued by the control computer 216 of the OBU 215) and the set of relays that operate for each command. In an embodiment, the data management unit 244 may generate the command relay list based on the set of in-vehicle unit data received in step S305 and the correspondence table generated in step S310. More specifically, for each command in the set of commands, the data management unit 244 determines which relay listed in the correspondence table is configured to operate for that command and generates a command relay list showing the relays that operate for each command. In an embodiment, the data management unit 244 may determine which relay operates for which command based on pre-prepared specification information for each relay (for example, a manufacturer-provided specification table). In this way, a command relay list showing which relay operates for each command in the set of commands included in the in-vehicle unit data collected from the OBU can be generated.

[0048] Next, in step S320, the data analysis unit 246 determines a relay operation count indicating the number of times each relay in the relay set has operated, based on the command relay list generated in step S315 and the set of command data included in the on-board unit data received in step S305. More specifically, the data analysis unit 246 may use the command relay list to determine which relay operates for each command in the set of command data and maintain a record indicating the number of times each relay has operated. These records for each relay may be summed up to generate a set of relay operation count data indicating the relay operation count for each relay. In embodiments, the relay operation count for each relay may be combined with a set of relay operation count data generated in the past to maintain an accurate representation of the number of times each relay has operated throughout its service life. In this way, even if the relays do not include an operation count function, the service life status regarding the number of operations of each relay in the relay rack set in the OBU can be determined and managed.

[0049] Next, in step S325, the data management unit 244 generates a rack error list showing the relationship between error types and sets of relay racks. In an embodiment, the data management unit 244 may generate the rack error list based on a set of error data included in the set of in-vehicle unit data received in step S305. More specifically, for each error listed in the set of error data, the data management unit 244 may determine which relays listed in the correspondence table are associated with that error and generate a rack error list showing each relay affected by that particular error type. In an embodiment, the data management unit 244 may determine which relays are associated with a particular error type based on pre-prepared specification information for each relay (e.g., a manufacturer-provided specification table). In this way, a rack error list showing which relays are affected by which error types can be generated.

[0050] Next, in step S330, the data analysis unit 246 determines an error count indicating the number of times an error occurred for each relay frame in the set of relay frames, based on the rack error list generated in step S325, the set of error data included in the in-vehicle unit data received in step S305, and the correspondence table generated in step S310. More specifically, the data analysis unit 246 may use the rack error list to determine the relay associated with the error type for each error in the error dataset, use the correspondence table to identify a specific relay frame (e.g., rack serial number) containing the affected relay, sum the total number of errors that occurred for each relay in each relay frame, and generate a set of error count data indicating the number of times an error occurred for each relay frame in the set of relay frames. In embodiments, the error count for each relay frame may be combined with a set of previously generated error count data to maintain an accurate representation of the number of errors that occurred for each relay frame throughout its service life. In this way, the service life status can be determined and managed with respect to the number of errors that occurred for each relay frame in the OBU.

[0051] Next, in step S335, the maintenance management unit 248 determines a maintenance action for one or more relay racks in the set of relay racks. In an embodiment, the maintenance management unit 248 may determine a maintenance action for a particular relay rack (e.g., a first relay rack) if the relay operation count determined in step S320, the error count determined in S330, or the operating time included in the set of operating time data included in the set of in-vehicle unit data obtained in step S305 exceeds a predetermined threshold. Here, a maintenance action refers to a process, operation, activity, or procedure for managing a particular relay rack. In an embodiment, a maintenance action may include performing an inspection of the particular relay rack, replacing one or more relays in the particular relay rack, or repairing one or more relays in the particular relay rack. In a particular embodiment, the maintenance action may be determined based on whether the relay operation count, the determined error count, or the operating time exceeds a predetermined threshold. For example, if, with respect to a particular relay rack, the relay operation count and operating time do not exceed a predetermined threshold, but the error count exceeds a predetermined threshold, the maintenance management unit 248 may decide to perform an inspection on that particular relay rack. Conversely, if the relay operation count and operating time exceed a predetermined threshold, but the error count does not exceed a predetermined threshold, the maintenance management unit 248 may decide to perform a replacement operation on that particular relay rack.

[0052] In addition, the predetermined threshold here refers to a criterion that defines the boundary for determining when a particular relay rack requires maintenance. In certain embodiments, the predetermined threshold may include individual thresholds set for relay operation count, error count, and operation time, respectively. Examples of predetermined thresholds for relay operation count, error count, and operation time will be described later, so their explanations will be omitted here.

[0053] In certain embodiments, the maintenance management unit 248 may calculate a total maintenance score indicating the likelihood that a first relay rack requires maintenance, based on the relay operation count, error count, and operating time of a particular relay rack. Here, in certain embodiments, the total maintenance score may be calculated by normalizing the relay operation count, error count, and operating time and performing a weighted average. In certain embodiments, the total maintenance score may be calculated using a machine learning technique that has been trained to identify relay racks requiring maintenance using training data, including relay operation counts, error counts, and operating times collected in the past. The total maintenance score may be expressed as a percentage value between 0 and 100%, with higher values ​​indicating a higher likelihood of requiring maintenance. The method used to calculate the total maintenance score is not particularly limited herein, and existing statistical or machine learning techniques may also be used.

[0054] In this embodiment, the maintenance management unit 248 may be configured to reset the relay operation count, error count, and operating time of a particular relay rack to zero after a maintenance action on the relay rack is completed. In this way, the usage characteristics of a particular relay rack can be updated to reflect changes in the service life of the relay rack due to the performance of the maintenance action.

[0055] According to the predictive maintenance method 300 described above, even if the relays do not include an operation counting function, it becomes possible to identify relay racks that have relays requiring maintenance. Furthermore, according to the predictive maintenance method 300, it is possible to detect relay racks that have relays requiring maintenance based not only on the number of operations performed, but also on information regarding the number of errors that occurred for each relay rack, and the total operating duration of a particular relay rack can also be taken into consideration. In this way, a more reliable representation of the current state of service life for the relays in each relay rack can be obtained.

[0056] Next, with reference to Figure 4, a correspondence table according to the embodiments of this disclosure will be described.

[0057] Figure 4 shows a correspondence table 400 according to an embodiment of the present disclosure. As described herein, the correspondence table 400 is a data table showing the relationships between train-mounted units, sets of relay racks, and sets of relays. The correspondence table 400 may be generated by the data management unit 244 of the predictive maintenance device 240 based on the set of on-board unit data and the set of relay rack identification information and stored in the storage unit 250 shown in Figure 2.

[0058] As shown in Figure 4, correspondence table 400 includes railway vehicle number 402, OBU number 404, rack type 406, rack serial number 408, and relay name 410.

[0059] Railway vehicle number 402 is a number that uniquely identifies a particular railway vehicle. For example, railway vehicle number 402 may include "Train 1" and "Train 2" as numbers to identify a particular railway vehicle.

[0060] OBU number 404 is a number that uniquely identifies a specific OBU on a particular railway vehicle. For example, OBU number 404 may include "OBU 1" and "OBU 2" as numbers that uniquely identify a particular OBU installed on a particular railway vehicle.

[0061] Rack type 406 is information that identifies the type of relay rack for a particular OBU. For example, rack type 406 may include TIU racks, RLU racks, etc. Rack serial number 408 is information used to uniquely identify a specific relay rack contained within a particular OBU. For example, rack serial number 408 may include "TIU-001", "RLU-002", etc.

[0062] Relay name 410 is information used to identify a specific relay included in a specific relay rack of a specific OBU. For example, relay name 410 may include "EB relay," "SB relay," "relay 2," etc.

[0063] According to the correspondence table 400 shown in Figure 4, it is possible to determine the correspondence between OBUs, relay racks, and relays for each railway vehicle in the railway network. As described herein, this correspondence table can be used to facilitate the generation of command relay lists, relay operation counts, and error counts, which are used to define the current state of the service life of a particular relay rack.

[0064] Next, with reference to Figure 5, a command relay list according to an embodiment of the present disclosure will be described.

[0065] Figure 5 shows a command relay list 500 according to an embodiment of the present disclosure. As described herein, the command relay list 500 is a data table showing the relationship between a set of commands exemplified by a particular OBU and a set of relays that operate for each command. The command relay list 500 may be generated by a data management unit 244 of a predictive maintenance device 240 based on a set of on-board unit data and stored in a storage unit 250 shown in Figure 2.

[0066] As shown in Figure 5, the command relay list 500 includes information about the command set 502 and the operating relay 504. Set of instructions 502 are instructions issued by the OBU of a particular railway vehicle to operate one or more relays in a set of relay racks. For example, the set of instructions may include "Instruction 1" and "Instruction 2". The operating relay 504 indicates a specific relay that operates in response to a specific command. For example, according to the command relay list 500, "Relay 1", "Relay 2", and "Relay 3" operate in response to "Command 1", and "Relay 1" and "Relay 4" operate in response to "Command 2".

[0067] According to the command relay list 500 shown in Figure 5, it is possible to determine which relays in a particular relay rack operate in response to which commands from the control computer 216 of the OBU 215. As described herein, this correspondence between the set of commands 502 and the operating relays 504 can be used to calculate the number of types of operations performed by each relay, facilitating monitoring of the service life of the set of relay racks.

[0068] Next, with reference to Figure 6, the set of relay operation count data according to the embodiment of this disclosure will be described.

[0069] Figure 6 shows a set of relay operation count data 600 according to an embodiment of the present disclosure. As described herein, the set of relay operation count data is a data table indicating the number of times one or more relays in a set of relay racks have operated. The set of relay operation count data 600 may be generated by the data analysis unit 246 of the predictive maintenance device 240 based on a set of command relay list 500, correspondence table 400, and command data set, which are included in a set of onboard unit data collected from the OBU 215.

[0070] As shown in Figure 6, the relay operation count data set 600 includes the railway vehicle number 602, the OBU number 604, the rack type 606, the rack serial number 608, the relay name 610, and the relay operation count 612. Railway vehicle number 602, OBU number 604, rack type 606, rack serial number 608, and relay name 610 substantially correspond to railway vehicle number 402, OBU number 404, rack type 406, rack serial number 408, and relay name 410 shown in correspondence table 400, so a detailed explanation of them is omitted here.

[0071] The relay operation count 612 is information indicating the number of times a particular relay has operated. For example, as shown in Figure 6, according to the relay operation count data set 600, the EB relay of relay rack "TIU-001" in "OBU 1" on "Train 1" has operated 1000 times, and the SB relay of relay rack "TIU-002" in "OBU 2" on "Train 2" has operated 1400 times.

[0072] The relay operation count data set 600 allows for the maintenance of information regarding the number of times each relay in a particular relay rack in a particular OBU has operated. As described herein, this relay operation count data set 600 can be used to monitor the service life of relays in a relay rack and facilitate the determination of maintenance actions for specific relays (e.g., relays nearing the end of their service life).

[0073] Next, with reference to Figure 7, the set of relay operation count threshold data according to the embodiment of this disclosure will be described.

[0074] As described herein, aspects of this disclosure relate to determining maintenance actions for a particular relay rack (e.g., a first relay rack) when the relay operation count, error count, or operation time included in a set of operation time data for that relay rack exceeds a predetermined threshold. The predetermined threshold may be set individually in advance for each of the relay operation count, error count, and operation time. Accordingly, Figure 7 shows a set of relay operation count threshold data 700 according to an embodiment of this disclosure.

[0075] The relay operation count threshold data set 700 is a data table for managing relay operation count threshold data for each relay in a set of relay racks. As shown in Figure 7, the relay operation count threshold data set 700 may include the railway vehicle number 702, the OBU number 704, the rack type 706, the rack serial number 708, the relay name 710, the relay operation count 712, and the relay operation count threshold 714. The railway vehicle number 702, OBU number 704, rack type 706, rack serial number 708, relay name 710, and relay operation count 712 substantially correspond to the railway vehicle number 602, OBU number 604, rack type 606, rack serial number 608, relay name 610, and relay operation count 612 shown in relay operation count data set 600, so a detailed explanation of them is omitted here.

[0076] The relay operation count threshold 714 is information indicating a specific relay operation count that defines a boundary for determining when a particular relay requires maintenance. The relay operation count threshold 714 may be defined individually for each relay in a set of relay racks. In embodiments, the relay operation count threshold may be determined based on estimated service life information provided in the specifications information for each relay (e.g., the manufacturer's specifications table). In certain embodiments, the relay operation count threshold may be determined based on historical usage data for each of the relays. As described herein, aspects of this disclosure relate to determining a maintenance action for a first relay when its relay operation count exceeds a corresponding relay operation count threshold. As an example, referring to Figure 7, the relay operation counter for an "SB relay" associated with a relay rack having rack serial number "TIU-001" in OBU 1 is "12,000", and the relay operation count threshold for this relay is "10,000", so this relay may be identified as a target for maintenance action.

[0077] In this way, using the set of relay operation count threshold data 700, it is possible to determine a maintenance action for the relay rack having those relays when the relay operation count exceeds a predetermined relay operation count threshold.

[0078] Next, with reference to Figure 8, a rack error list according to an embodiment of the present disclosure will be described.

[0079] Figure 8 shows a rack error list 800 according to an embodiment of the present disclosure. As described herein, the rack error list 800 is a data table showing the relationship between error types and sets of relay racks. The rack error list 800 may be generated by the data management unit 244 of the predictive maintenance device 240 based on a set of error data included in a set of onboard unit data and / or pre-prepared standard information for each relay (e.g., a manufacturer's standard table).

[0080] As shown in Figure 8, the rack error list 800 includes information about the relay rack 802 and error type 804. Relay rack 802 indicates a specific relay rack or the type of relay rack included in a specific OBU unit. For example, relay rack 802 may include information about the relay rack type, such as "TIU rack" and "RLU rack". Error type 804 indicates a specific type of error associated with a particular relay rack or type of relay rack. For example, according to rack error list 800, "TIU rack" is associated with "Error 1" and "Error 2," and "RLU rack" is associated with "Error 3," "Error 4," and "Error 5."

[0081] According to the rack error list 800 shown in Figure 8, it is possible to maintain data that specifies which relays are affected by which types of errors. As described herein, this information can be used to determine the number of errors that have occurred in each relay of a set of relay racks.

[0082] Next, with reference to Figure 9, the set of error count data according to the embodiment of this disclosure will be described.

[0083] Figure 9 shows a set 900 of error count chambers according to an embodiment of the present disclosure. As described herein, the set 900 of error count data may include a data table indicating the number of times an error has occurred for each relay rack in a set of relay racks. In embodiments, the set of error count data may also include information indicating a defined error threshold for each relay rack. The set 900 of error count data may be generated by the data analysis unit 246 of the predictive maintenance device 240 based on a rack error list, correspondence table, and set of error data included in the on-board unit data.

[0084] As shown in Figure 9, the error count data set 900 may include the railway vehicle number 902, the OBU number 904, the rack type 906, the rack serial number 908, the relay name 910, the error count 912, and the error count threshold 914. Railway vehicle number 902, OBU number 904, rack type 906, rack serial number 908, and relay name 910 substantially correspond to railway vehicle number 702, OBU number 704, rack type 706, rack serial number 708, and relay name 710 shown in relay operation count threshold data set 700, so a detailed explanation of them is omitted here.

[0085] Error count 912 indicates the number of times an error occurred for a particular relay rack. For example, as shown in Figure 9, according to error count data set 900, four errors occurred for the "TIU rack" of "OBU 1" on "Train 1".

[0086] The error count threshold 914 is information indicating a specific error count that defines a boundary for determining when a particular relay rack requires maintenance. The error count threshold 914 may be defined individually for each relay rack in a set of relay racks. In embodiments, the error count threshold 914 may be determined based on estimated service life information provided in the specifications information (e.g., the manufacturer's specifications table) for each relay in a particular relay rack. In certain embodiments, the error count threshold 914 may be determined based on historical usage data for each relay in a particular relay rack. As described herein, aspects of the disclosure relate to determining maintenance action for a first relay rack when the error count for that relay rack exceeds a corresponding error count threshold. As an example, referring to Figure 9, the error count 012 for the "TIU rack" in OBU 2 of train 2 is "31", and the relay operation count threshold for this relay is "30", so this relay rack may be identified as a target for maintenance action.

[0087] In this way, using the error count data set 900, it is possible to determine a maintenance action for a relay rack when the number of errors that occur on that rack exceeds a predetermined error count threshold.

[0088] Next, with reference to Figure 10, the set of relay rack usage data according to the embodiment of this disclosure will be described.

[0089] Figure 10 shows a set of relay rack usage data 1000 according to an embodiment of the present disclosure. The set of relay rack usage data 1000 may include a data table that includes the usage characteristics of a set of relay racks for one or more OBUs. In the embodiment, the set of relay rack usage data 1000 may be generated by summing a set of relay operation count threshold data 700, a set of error count data 900, and operation time data included in a set of OBU data received from a particular OBU.

[0090] As shown in Figure 10, the relay rack usage data set 1000 may include the railway vehicle number 1002, OBU number 1004, rack type 1006, rack serial number 1008, relay name 1010, relay operation count 1012, relay operation count threshold 1014, error count 1016, error threshold 1018, rack operation time 1020, and rack operation time threshold 1022. Note that the railway vehicle number 1002, OBU number 1004, rack type 1006, rack serial number 1008, relay name 1010, relay operation count 1012, relay operation count threshold 1014, error count 1016, and error threshold 1018 substantially correspond to those described with reference to Figures 6, 7, and 9, and therefore their detailed explanations are omitted here.

[0091] Rack operating time 1020 is information indicating the length of time (e.g., how many hours) each relay rack in a set of relay racks was in operation. In the embodiment, each OBU may maintain a record of the total number of hours each of its relay racks was in operation and include this information in the set of in-vehicle unit data acquired by the data acquisition unit 242. As an example, referring to Figure 10, the relay rack associated with rack serial number RLU-001 in OBU 1 was in operation for a total of 400 hours.

[0092] The rack operating time threshold 1022 is information indicating a specific rack operating time that defines a boundary for determining when a particular relay rack requires maintenance. The rack operating time threshold 1022 may be defined individually for each relay rack in a set of relay racks. In an embodiment, the rack operating time threshold 1022 may be determined based on estimated service life information provided in the standard information for each relay in a particular relay rack. In a particular embodiment, the rack operating time threshold 1022 may be determined based on historical usage data for each relay in a particular relay rack.

[0093] As described herein, aspects of this disclosure relate to determining maintenance actions for a particular relay rack (e.g., a first relay rack) when the relay operation count, error count, or operation time included in the set of operation time data for that relay rack exceeds a predetermined threshold. Accordingly, in embodiments, the maintenance management unit 248 may use the rack operation time threshold 1022 to identify any relay rack whose relay operation count, error count, or operation time exceeds the corresponding threshold. For example, as shown in Figure 10, the relay operation count and error count for a relay rack having rack serial number "TIU-002" in OBU 2 of train 2 do not exceed the corresponding threshold, but the rack operation time of 41,000 hours exceeds the rack operation time threshold of 40,000 hours, so the maintenance management unit 248 may decide to perform maintenance action on this relay rack.

[0094] In certain embodiments, after determining a maintenance action for a specific relay rack, the maintenance management unit 248 may generate a maintenance notification indicating the determined maintenance action, the relay rack on which the maintenance action should be performed, and a set of relay rack usage data 1000, and send it to the user terminal 220 for confirmation. In this embodiment, the maintenance management unit 248 may be configured to reset the relay operation count, error count, and operating time of a specific relay rack to zero in the relay rack usage data set 1000 after the maintenance action on the relay rack is completed. In this way, the usage characteristics of a specific relay rack can be updated to reflect changes in the service life of the relay rack due to the performance of the maintenance action.

[0095] According to the relay rack usage data set 1000, it is possible to maintain information regarding various usage characteristics for each relay in each relay rack of a set of relay racks for one or more OBUs. Furthermore, as described herein, this relay rack usage data set 1000 can be used to facilitate the identification of specific relay racks for which maintenance actions should be taken, taking into account usage characteristics and estimated service life. Note that in addition to the information shown in Figure 10, the relay rack usage data set 1000 may include additional information regarding the usage characteristics of sets of relays and sets of relay racks. For example, in an embodiment, the relay rack usage data set 1000 may include a maintenance score calculated for each relay rack based on relay operation count, error count, and operating time.

[0096] As described herein, aspects of this disclosure relate to providing predictive maintenance techniques for managing the relay service life of OBU relay racks that are not equipped with operation counting functions. More specifically, aspects of this disclosure relate to determining the number of times each relay in one or more relay racks in an OBU has operated, based on command data received from the OBU and a command-relay list showing the relationship between a particular command and a particular relay. In this way, it is possible to identify relay racks that have operated more times than a target threshold for maintenance operation.

[0097] According to the predictive maintenance technique of the present disclosure, a relay rack having a relay requiring maintenance can be detected not only based on the number of operations performed, but also based on information regarding the number of errors that occurred for each relay in the relay rack, and the total operating duration of a particular relay rack. In this way, a more reliable representation of the current state of the service life of the relays in each relay rack can be obtained. In addition, the maintenance action to be performed on a particular relay rack may be determined based on whether the relay operation count, error count, or operating time exceeds a threshold. Therefore, maintenance actions that are specifically tailored to the operating state of the relay rack can be selected. Furthermore, in a configuration where the railway vehicle 210 and the predictive maintenance device 240 are configured for direct communication via the communication network 230, it should be noted that the data acquisition unit 242 may directly send data acquisition requests to the railway vehicle 210 in order to dynamically acquire a set of onboard unit data. In this way, the service life of the relays on each relay track can be monitored in real time, and maintenance actions on the relay racks can be quickly determined while the railway vehicle 210 is in operation, without having to wait for the railway vehicle 210 to arrive at the station.

[0098] In this way, embodiments of the present disclosure make it possible to provide a predictive maintenance technique for managing the relay service life of OBU relay racks that are not equipped with an operation counting function. As a result, the safety and efficiency of railway vehicle operation can be promoted.

[0099] As described herein, this disclosure relates to the following embodiments.

[0100] (Aspect 1) A predictive maintenance system for a train-mounted unit, wherein the predictive maintenance system is A train-mounted unit installed on the train, The system includes a predictive maintenance device for determining maintenance actions for the train-mounted unit, The aforementioned train-mounted unit, Includes a set of relay racks, each containing a set of relays, Includes a control computer for outputting commands to operate the set of relays in the set of relay racks, It does not include a relay operation counting function for counting the number of operations of the aforementioned set of relays. The predictive maintenance device, A data acquisition unit for collecting a set of in-vehicle unit data, which includes at least a set of command data indicating a set of commands output by the control computer to the set of relay racks in order to operate the set of relays, A data management unit for generating a command relay list that shows the relationship between the set of commands and the set of relays that operate for each command, A data analysis unit for determining a relay operation count indicating the number of operations for each relay in the set of relays, based on the command relay list and the set of command data, A predictive maintenance system comprising: a maintenance management unit for determining a maintenance action for a first relay rack when the relay operation count of a first relay rack among the set of relay racks exceeds a predetermined threshold;

[0101] (Aspect 2) A predictive maintenance system according to Embodiment 1, wherein the set of in-vehicle unit data is A set of error data indicating the presence or absence of errors for each rack in the relay rack set, A predictive maintenance system further includes an operating time indicating the operating duration of a set of relay racks in a train-mounted unit.

[0102] (Aspect 3) A predictive maintenance system according to embodiment 2, wherein the data management unit is Based on the set of onboard unit data and the set of relay rack identification information, a correspondence table is generated showing the relationships between the train onboard units, the relay rack sets, and the relay sets. A command relay list is generated based on a set of in-vehicle unit data. A predictive maintenance system that determines relay operation counts based on a command relay list, a set of command data, and a correspondence table.

[0103] (Aspect 4) A predictive maintenance system according to Embodiment 3, The data management unit, Based on the set of error data, a rack error list is generated that shows the relationship between the error type and the set of relay racks. The data analysis unit, A predictive maintenance system that uses a rack error list, a set of error data, and a correspondence table to determine an error count indicating the number of errors for each rack in a set of relay racks.

[0104] (Appendix 5) A predictive maintenance system according to embodiment 4, wherein the maintenance management unit is A predictive maintenance system that determines a maintenance action for a first relay rack when the relay operation count, error count, or operating time of the first relay rack exceeds a predetermined threshold.

[0105] (Aspect 6) A predictive maintenance system according to embodiment 4, wherein the maintenance management unit is Based on the relay operation count, error count, and operating time of the first relay rack, a total maintenance score is calculated that indicates the likelihood that the first relay rack requires maintenance. A predictive maintenance system that determines a maintenance action for a first relay rack when the relay operation count exceeds a predetermined maintenance score threshold.

[0106] (Aspect 7) A predictive maintenance system according to any one of embodiments 4 to 6, wherein the maintenance management unit is A predictive maintenance system that, after maintenance action on the first relay rack is completed, resets the relay operation count, error count, and operation time of the first relay rack to zero.

[0107] The present invention may be a system, a method, a computer program product, or a combination thereof. The computer program product may include a computer-readable storage medium (or a combination of mediums) having computer-readable program instructions that cause a processor to implement aspects of the present invention.

[0108] A computer-readable storage medium can be a tangible device capable of holding and storing instructions used by an instruction execution device. A computer-readable storage medium may, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any preferred combination of the above. A non-exclusive list of more specific examples of computer-readable storage media includes portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multipurpose discs (DVDs), memory sticks, floppy disks, mechanically encoded devices such as punched cards or grooved raised structures on which instructions are recorded, and any preferred combination of the above. Computer-readable storage media, when used herein, shall not be construed as transient signals in themselves, such as high-frequency or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.

[0109] Aspects of the present invention are described herein with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It will be understood that each block in the flowcharts and / or block diagrams, as well as combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0110] Computer-readable program instructions may be provided to the processor of a general-purpose computer, a dedicated computer, or other programmable data processing device for manufacturing a machine, thereby creating means for the instructions to be executed via the processor of the computer or other programmable data processing device to realize a function / operation specified in one or more blocks of a flowchart and / or block diagram. These computer-readable program instructions may also be stored in a computer-readable storage medium, which can instruct a computer, a programmable data processing device, and / or other device to function in a particular manner, thereby including a product in which the computer-readable storage medium containing the instructions includes instructions that realize a mode of function / operation specified in one or more blocks of a flowchart and / or block diagram.

[0111] Computer-readable program instructions may also be loaded into a computer, other programmable data processing device, or other device to perform a series of operational steps on the computer, other programmable device, or other device, thereby creating a computer implementation process in which the instructions executed on the computer, other programmable device, or other device realize a function / operation specified in one or more blocks of a flowchart and / or block diagram.

[0112] The flowcharts and block diagrams in the drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions that implement a specified logical function. In some alternative implementations, the functions shown in the blocks may be performed in an order other than that shown in the drawings. For example, two consecutively shown blocks may actually be executed substantially simultaneously, depending on the functionality involved, or the blocks may be executed in reverse order. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by an application-specific hardware-based system that performs a specified function or operation, or by a combination of application-specific hardware and computer instructions.

[0113] While the above describes illustrative embodiments, other and further embodiments of the present invention may be devised without departing from the basic scope of the invention, the scope of which is determined by the following claims. The various embodiments described in this disclosure are presented for illustrative purposes only and are not intended to be exclusive or limiting to the embodiments disclosed. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the embodiments described. The terminology used herein has been selected to describe the principles of the embodiments, their practical applications, or technical improvements to technologies available on the market, or to enable those skilled in the art to understand the embodiments disclosed herein.

[0114] The technical terms used herein are for describing specific embodiments only and are not intended to limit the various embodiments. Where used herein, the singular forms "a," "an," and "the" also include the plural form unless otherwise specified by context. "Set of," "group of," "cluster of," etc., include one or more. Furthermore, where used herein, the terms "include" and / or "contain" specify the existence of the presented features, integers, steps, actions, elements, and / or components, but do not exclude the existence or addition of one or more other features, integers, steps, actions, elements, components, and / or groups thereof. In the above detailed descriptions of exemplary embodiments among the various embodiments, references are made to the accompanying drawings (similar numbers represent similar elements) illustrating specific exemplary embodiments that form part of this disclosure and in which various embodiments may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice this disclosure, but other embodiments may be used, and modifications may be made without departing from the scope of the various embodiments. The above description includes numerous specific details to provide a complete understanding of the various embodiments. However, various embodiments may be practiced without these specific details. In other examples, well-known circuits, structures, and techniques are not shown in detail so as not to obscure the embodiments. [Explanation of symbols]

[0115] 200: Predictive maintenance system 210: Railway vehicles 215: Vehicle-mounted unit 216: Control computer 217: Relay rack set 220: User terminal 230: Communication Network 240: Predictive maintenance devices 242: Data acquisition unit 244: Data Management Unit 246: Data Analysis Unit 248: Maintenance Management Unit 250: Storage Unit

Claims

1. A predictive maintenance system for a train-mounted unit, wherein the predictive maintenance system is A train-mounted unit installed on the train, The system includes a predictive maintenance device for determining maintenance actions for the train-mounted unit, The aforementioned train-mounted unit, Includes a set of relay racks, each containing a set of relays, Includes a control computer for outputting commands to operate the set of relays in the set of relay racks, It does not include a relay operation counting function for counting the number of operations of the aforementioned set of relays. The predictive maintenance device, A data acquisition unit for collecting a set of in-vehicle unit data, which includes at least a set of command data indicating a set of commands output by the control computer to the set of relay racks in order to operate the set of relays, A data management unit for generating a command relay list that shows the relationship between the set of commands and the set of relays that operate for each command, A data analysis unit for determining a relay operation count indicating the number of operations for each relay in the set of relays, based on the command relay list and the set of command data, A predictive maintenance system comprising: a maintenance management unit for determining a maintenance action for a first relay rack when the relay operation count of a first relay rack among the set of relay racks exceeds a predetermined threshold;

2. The set of in-vehicle unit data is A set of error data indicating the presence or absence of errors for each rack in the relay rack set, The operating time of the relay rack set of the train-mounted unit indicates the operating duration and The predictive maintenance system according to claim 1, further comprising:

3. The aforementioned data management unit Based on the set of onboard unit data and the set of relay rack identification information, a correspondence table is generated showing the relationship between the train onboard unit, the set of relay racks, and the set of relays. Based on the set of in-vehicle unit data, the command relay list is generated. The relay operation count is determined based on the command relay list, the command data set, and the correspondence table. The predictive maintenance system according to claim 2.

4. The aforementioned data management unit Based on the set of error data, a rack error list is generated that shows the relationship between the error type and the set of relay racks. The aforementioned data analysis unit, Using the rack error list, the set of error data, and the correspondence table, an error count indicating the number of errors for each rack in the set of relay racks is determined. The predictive maintenance system according to claim 3.

5. The aforementioned maintenance management unit When the relay operation count, error count, or operation time of the first relay rack exceeds a predetermined threshold, a maintenance action related to the first relay rack is determined. The predictive maintenance system according to claim 4.

6. The aforementioned maintenance management unit Based on the relay operation count, error count, and operating time of the first relay rack, a total maintenance score is calculated that indicates the likelihood that the first relay rack requires maintenance. When the relay operation count exceeds a predetermined maintenance score threshold, the maintenance action for the first relay rack is determined. The predictive maintenance system according to claim 4.

7. The aforementioned maintenance management unit After the maintenance action on the first relay rack is completed, the relay operation count, error count, and operation time of the first relay rack are reset to zero. The predictive maintenance system according to claim 4.

8. A predictive maintenance method for a train-mounted unit, wherein the train-mounted unit is Includes a set of relay racks, each containing a set of relays, Includes a control computer for outputting commands to operate the set of relays in the set of relay racks, It does not include a relay operation counting function for counting the number of operations of the aforementioned set of relays. The aforementioned predictive maintenance method This involves collecting a set of onboard unit data from the aforementioned train onboard unit, A set of command data indicating a set of commands output by the control computer to the set of relays in order to operate the set of relays, A set of error data indicating the presence or absence of errors for each rack in the relay rack set, The collection of a set of onboard unit data, including the operating time, which indicates the operating duration of the relay rack set of the onboard train unit, Based on the set of onboard unit data and the set of relay rack identification information, a correspondence table is generated showing the relationship between the train onboard unit, the set of relay racks, and the set of relays. Based on the set of in-vehicle unit data, a command relay list is generated that shows the relationship between the set of commands and the set of relays that operate for each command. Based on the command relay list, the command data set, and the correspondence table, a relay operation count is determined that indicates the number of operations for each relay in the relay rack set. Based on the set of error data, a rack error list is generated that shows the relationship between the error type and the set of relay racks. Using the rack error list, the set of error data, and the correspondence table, an error count indicating the number of errors for each rack in the set of relay racks is determined. A predictive maintenance method comprising determining a maintenance action for the first relay rack when the relay operation count, error count, or operation time of the first relay rack of the set of relay racks exceeds a predetermined threshold.

9. Based on the relay operation count, error count, and operating time of the first relay rack, a total maintenance score is calculated indicating the likelihood that the first relay rack requires maintenance. When the relay operation count exceeds a predetermined maintenance score threshold, the maintenance action for the first relay rack is determined. The predictive maintenance method according to claim 8, further comprising:

10. After the maintenance action for the first relay rack is completed, the relay operation count, error count, and operation time of the first relay rack are reset to zero. The predictive maintenance method according to claim 8, further comprising:

11. A predictive maintenance computer program for a train-mounted unit, wherein the train-mounted unit, Includes a set of relay racks, each containing a set of relays, Includes a control computer for outputting commands to operate the set of relays in the set of relay racks, It does not include a relay operation counting function for counting the number of operations of the aforementioned set of relays. The predictive maintenance computer program includes a computer-readable storage medium in which program instructions are embedded, the computer-readable storage medium is not essentially a transient signal, the program instructions are executable by a processor and cause the processor to perform a method, and the method This involves collecting a set of onboard unit data from the aforementioned train onboard unit, A set of command data indicating a set of commands output by the control computer to the set of relays in order to operate the set of relays, A set of error data indicating the presence or absence of errors for each rack in the relay rack set, The collection of a set of onboard unit data, including the operating time, which indicates the operating duration of the relay rack set of the onboard train unit, Based on the set of onboard unit data and the set of relay rack identification information, a correspondence table is generated showing the relationship between the train onboard unit, the set of relay racks, and the set of relays. Based on the set of in-vehicle unit data, a command relay list is generated that shows the relationship between the set of commands and the set of relays that operate for each command. Based on the command relay list, the command data set, and the correspondence table, a relay operation count is determined that indicates the number of operations for each relay in the relay rack set. Based on the set of error data, a rack error list is generated that shows the relationship between the error type and the set of relay racks. Using the rack error list, the set of error data, and the correspondence table, an error count indicating the number of errors for each rack in the set of relay racks is determined. A predictive maintenance computer program that includes determining a maintenance action for a first relay rack when the relay operation count, error count, or operation time of a first relay rack in a set of relay racks exceeds a predetermined threshold.

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